Ingeniero Civil Eléctrico / Las redes vehiculares ad-hoc (VANets) son un nuevo paradigma en comunicación móvil que se plantea que podría permitir el despliegue de sistemas de transporte inteligente (ITS), más seguros, eficientes y amigables con el medioambiente. Se cuenta con el estándar DSRC de comunicaciones vehiculares pero no está comprobado que sea capaz de ofrecer la robustez y seguridad que necesitan los ITS. Las comunicaciones por luz visible (VLCs), son tecnologías de comunicación inalámbricas basadas en la modulación de intensidad de luz. Se realizan con dispositivos opto-electrónicos como diodos LED y foto-diodos. Se plantea que éstas podrían complementar a las radio-frecuencias (RF), como las del protocolo DSRC, por ejemplo, y permitir a las VANets entregar un mejor servicio, sobre todo en ambientes congestionados. En el presente trabajo, se realizó el desarrollo de una plataforma con herramientas para prototipado de enlaces VLC con aplicación en VANets bajo la hipótesis que las tecnologías existentes de illuminación en automóviles y señales de tránsito son una infraestructura que permite implementar VLCs en ambientes vehiculares. Primero se consultó el estado del arte de VANets y de VLCs, enfocado en entender el origen del interés por la implementación de redes vehiculares, así como sus desafíos y cómo las VLCs pueden mejorar el desempeño de dichos sistemas. Se estudiaron tecnologías aplicables a los sistemas de información y comunicaciones de las redes vehiculares con enfoque en las VLC. Un grupo fueron las plataformas de hardware programable como radios definidas por software (SDRs) y las placas Arduino. Otro tema fue la red de control interna de los vehículos y cómo existen interfaces para acceder a ella y obtener mediciones de los sensores e incluso dar instrucciones a los actuadores del auto. También, se revisaron los transductores de una red VLC: los diodos LED y fotodiodos, incluyendo la electrónica necesaria para su funcionamiento. Finalmente, se implementó un sistema de comunicaciones por VLC, basado en SDRs y optoelectrónica, y también un sistema adquisición de datos para la red de control del vehículo, basado en Arduino y un circuito integrado ELM327. Ambos sistemas se diseñaron modulares y se construyeron robustos. Se logró con ellos la transmisión de datos por luz y la lectura de datos del area de control del vehículo. Actualmente, el sistema desarrollado está en manos de un grupo de investigación que se dedica a estudiar las tecnologías de comunicación vehicular. También se está trabajando en una publicación con la evaluación de los sistemas implementados. / Este trabajo ha sido parcialmente financiado por ERANet-LAC Proyecto "RETRACT" Código ELAC2015/T10-0761, FONDECYT iniciación N° 11160517, FONDECYT Posdoctorado N° 3170021

One of the most challenging issues facing vehicular networks lies in the design of an efficient MAC protocol due to mobile nature of nodes, delay constraints for safety applications and interference. In this thesis, I propose an efficient Multichannel QoS Cognitive MAC (MQOG). MQOG assesses the quality of channel prior to transmission employing dynamic channel allocation and negotiation algorithms to achieve significant increase in channel reliability, throughput and delay constraints while simultaneously addressing Quality of Service. The uniqueness of MQOG lies in making use of the free unlicensed bands. To consider fair effective sharing of resources I propose a Mobility Based Dynamic Transmit Opportunity (MoByToP) while modifying the 802.11e TXOP (Transmit Opportunity). The proposed protocols were implemented in OMNET++ 4.1, and extensive experiments demonstrated a faster and more efficient reception of safety messages compared to existing VANet MAC Protocols. Finally, improvements in delay, packet delivery ratios and throughput were noticed.

Behavioral patterns prediction in the context of Vehicular Ad hoc Networks (VANETs)has been receiving increasing attention due to enabling on-demand, intelligent traffic analysis and response to real-time traffic issues. One of these patterns, sequential patterns, are a type of behavioral patterns that describe the occurence of events in a timely-ordered fashion. In the context of VANETs, these events are defined as an ordered list of road segments traversed by vehicles during their trips from a starting point to their final intended destination, forming a vehicular path. Due to their predictable nature, undertaken vehicular paths can be exploited to extract the paths that are considered frequent. From the extracted frequent paths through data mining, the probability that a vehicular path will take a certain direction is obtained. However, in order to achieve this, samples of vehicular paths need to be initially collected over periods of time in order to be data-mined accordingly. In this thesis, a new set of formal definitions depicting vehicular paths as sequential patterns is described. Also, five novel communication schemes have been designed and implemented under a simulated environment to collect vehicular paths; such schemes are classified under two categories: Road Side Unit-Triggered (RSU-Triggered) and Vehicle-Triggered. After collection, extracted frequent paths are obtained through data mining, and the probability of these frequent paths is measured. In order to evaluate the e ciency and e ectiveness of the proposed schemes, extensive experimental analysis has been realized. From the results, two of the Vehicle-Triggered schemes, VTB-FP and VTRD-FP, have improved the vehicular path collection operation in terms of communication cost and latency over others. In terms of reliability, the Vehicle-Triggered schemes achieved a higher success rate than the RSU-Triggered scheme. Finally, frequent vehicular movement patterns have been effectively extracted from the collected vehicular paths according to a user-de ned threshold and the confidence of generated movement rules have been measured. From the analysis, it was clear that the user-de ned threshold needs to be set accordingly in order to not discard important vehicular movement patterns.

The transmitting of video content over Vehicular Ad Hoc Networks (VANETs) faces a great number of challenges caused by strict QoS (Quality of Service) requirements and highly dynamic network topology. In order to tackle these challenges, multipath forwarding schemes can be regarded as potential solutions. However, route coupling effect and the path length growth severely impair the performance of multipath schemes. In this thesis, the current research status about video streaming over VANETs as well as multipath transmissions are reviewed. With the demand to discover a more suitable solution, we propose the Location-Aware Multipath Video Streaming (LIAITHON+) protocol to address video streaming over urban VANETs. LIAITHON+ uses location information to discover relatively short paths with minimal route coupling effect. The performance results have shown it outperforms the underlying single path solution as well as the node-disjoint multipath solution. In addition, the impact of added redundancy on the multipath solution is investigated through LIAITHON+. According to the results, added redundancy has a different impact depending on the data rate.

Intelligent Transport System (ITS) has become a hot research topic over the past decades. ITS is a system that applies the following technologies to the whole transportation management system efficiently, including information technique, wireless communication, sensor networks, control technique, and computer engineering. ITS provides an accurate, real time and synthetically efficient transportation management system. Obviously, Vehicular Ad Hoc NETworks (VANETs) attract growing attention from both the research community and industry all over the world. This is because a large amount of applications are enabled by VANETs, such as safety related applications, traffic management, commercial applications and general applications. When connecting to the internet or communicating with different networks in order to access a variety of services using VANETs, drivers and passengers in different cars need to be able to exchange messages with gateways from their vehicles. A secure gateway discovery process is therefore critical, because vehicles should not be subject to security attacks while they are communicating; however, currently there is no existing protocol focusing on secure gateway discovery. In this thesis, we first analyze and compare current existing secure service discovery protocols and then we propose a Secure Gateway Localization and Communication System for Vehicular Ad Hoc Networks (SEGAL), which concentrates on the security issue in gateway discovery. We focus on the authentication aspect by proposing secure cluster based VANETs, that can ensure the gateway discovery messages exchanged through secure clusters. We present the principle and specific process of our SEGAL protocol and analyze its performance to guarantee its outstanding practical applicability.

VANETs are the essential component of the intelligent transport system, which attract research and industrial interests increasingly. As the multifunctional mobile nodes integrating transporting, sensing, information processing, and wireless communication capabilities, vehicular nodes are facing remarkable security issues and more vulnerable to malware attack than conventional communication nodes. In this thesis, the behavior and the security issues of the worm spreading on VANETs are studied. The approaches of the worm spreading on VANETs are discussed and an infrastructure based worm containment strategy is proposed. The infrastructure based worm containment problem is modeled as minimum contamination problem by introducing the expected contamination degree. Then the existing greedy method is applied to solve the proposed problem in VANETs scenario. After that, the Grid-shrinking Greedy Method and the Simplified Greedy Method are proposed which incorporate the characteristics of road networks and VANETs respectively. Simulation results show the two proposed methods outperform the existing greedy method and the comparison method from both complexity and solution quality aspects.

Vehicular communication is the enabling technology for the development of the intelligent transportation systems (ITS), which aims to improve the efficiency and safety of transportation. It can be used for a variety of useful applications such as adaptive traffic control, coordinated braking, emergency messaging, peer-to-peer networking for infotainment services and automatic toll collection etc... Accurate yet simple models for vehicular networks are required in order to understand and optimize their operation. For reliable communication between vehicles, the spectrum access is coordinated via carrier sense multiple access (CSMA) protocol. Existing models either use a simplified network abstraction and access control scheme for analysis or depend on simulation studies. Therefore it is important to develop an analytical model for CSMA coordinated communication between vehicles. In the first part of the thesis, stochastic geometry is exploited to develop a modeling framework for CSMA coordinated inter-vehicle communication (IVC) in a multi-lane highway scenario. The performance of IVC is studied in multi-lane highways taking into account the inter-lane separations and the number of traffic lanes and it is shown that for wide multi-lane highways, the line abstraction model that is widely used in literature loses accuracy and hence the analysis is not reliable. Since the analysis of CSMA in the vehicular setting makes the analysis intractable, an aggressive interference approximation and a conservative interference approximation is proposed for the probability of transmission success. These approximations are tight in the low traffic and high traffic densities respectively. In the subsequent part of the thesis, the developed model is extended to multi-hop IVC because several vehicular applications require going beyond the local communication and efficiently disseminate information across the roads via multi-hops. Two well-known greedy packet forwarding schemes are studied, that impose different tradeoffs between per-hop transmission success probability and forward packet progress, namely, the most forward with fixed radius (MFR) and the nearest with forward progress (NFP). In particular, a tractable and accurate modeling framework is developed to characterize the per-hop transmission success probability and the average forward progress for vehicular networks in a multi-lane highway setup. The developed model reveals the interplay between the spectrum sensing threshold of the CSMA protocol and the packet forwarding scheme. A new performance metric is defined, denoted as the aggregate packet progress (APP), which is a dimensionless quantity that captures the tradeoffs between the spatial frequency reuses efficiency, the per-hop transmission success probability, and the per-hop forward progress of the packets. To this end, in contrary to existing studies, the results show that with the proper manipulation of CSMA threshold, the MFR achieves the highest APP.

Blockchain's use in Vehicular Ad-Hoc Networks (VANETs) research demonstrates that the technology provides useful attributes to allow for the safe and secure operation of VANET applications. The growth of blockchain applications pose a threat to the efficient operation of the MANET-like environment found within VANETs. Floating Genesis Blocks (FGB) can be used to preserve the state of the blockchain up to a certain point, and allows for the safe pruning of the chain without information loss. The early work presented here demonstrates two pruning techniques and compares the effects of each blockchain through simulation measurement of the chain's space requirements. A discussion on the results and recommendations for future work conclude the author's work.

Security is a necessity when dealing with new forms of technology that may not have been analyzed from a security perspective. One of the latest growing technological advances are Vehicular Ad-Hoc Networks (VANETs). VANETs allow vehicles to communicate information to each other wirelessly which allows for an increase in safety and efficiency for vehicles. However, with this new type of computerized system comes the need to maintain security on top of it. In order to try to protect location privacy of the vehicles in the system, vehicles change pseudonyms or identifiers at areas known as mix zones. This thesis implements a model that characterizes the attack surface of an adversarial insider vehicle inside of a VANET. This adversarial vehicle model describes the interactions and effects that an attacker vehicle can have on mix zones in order to lower the overall location privacy of the system and remain undetected to defenders in the network. In order to reach the final simulation of the model, several underlying models had to be developed around the interactions of defender and attacker vehicles. The evaluation of this model shows that there are significant impacts that internal attacker vehicles can have on location privacy within mix zones. From the created simulations, the results show that having one to five optimal attackers shows a decrease of 0.6%-2.6% on the location privacy of the network and a 12% decrease in potential location privacy in a mix zone where an attacker defects in a 50-node network. The industry needs to consider implementing defenses based on this particular attack surface discussed.

With the dramatic growth of vehicles around the world, Vehicular Ad-hoc Networks (VANETs) have been proposed as a solution to advance road safety, improve transportation efficiency, and satisfy road users. In the VANET environment, vehicles communicate with each other and with road infrastructure in an ad-hoc manner. This communication may be safety-related or non-safety-related and may often include vehicle information (e.g., location, direction, speed, and control), road conditions, and events. A key component in assessing the veracity of the information is the trustworthiness of the information source. Thus, trust evaluation is one of the main requirements of VANET design. In this work, we investigate performance improvements in the trust evaluation framework of VANETs. First, we propose a risk-based trust evaluation model (RTEAM) to estimate the risk of taking action or refraining from action regarding a reported event (in case of receiving conflicting messages about the event's existence). Some trust metrics such as direct trust, hop-based trust values, proximity to the event, and consequences of acting on a wrong decision are used to estimate the risk of the vehicle’s actions. Vehicles make individual decisions by seeking the action with the lowest risk. Second, we propose a fog-based reputation evaluation model (FREM) to support trust management framework. We promote fog computing as a new paradigm since it can provide several services to users in the edge layer. In our work, Fog supports the decision-making process in the reputation evaluation framework. Fog nodes play a key role in collecting vehicles' reputation records and cooperating with the roadside units (RSUs) to update these records. We propose the use of Digital Trustworthiness Cards (DTC), where the latest reputation evaluation of a vehicle automatically appears on its card. The benefits of the DTC are twofold: 1) the communication load on vehicles is reduced, and 2) historical trust records are established for each vehicle. We also take advantage of fog’s familiarity and greater knowledge of the vehicles that frequently visit its zones; with more intimate knowledge, fog can smartly employ vehicles to perform specific tasks based on their experiences. Further, we implement a strategy for establishing trust based on specific task categories. This permits a nuanced evaluation of the vehicle best suited for the task at hand and has the further benefit of preventing malicious vehicles from being naively trusted based on successful completion of unimportant or non-safety-related tasks. Finally, we expand the role of the fog in the decision-making process when vehicles need to ensure the existence of serious events. We propose a fog-based event validation model (FEVM) to validate the event’s existence through cooperation between vehicles and fog nodes. The vehicles are used as mobile fog nodes, which compute their confidence in events based on the available information. Fog nodes then validate the event after combining vehicles’ confidence values by applying the Extended Dempster-Shafer (EDS) theory of evidence. To test our proposed models, we conduct many experiments to investigate their performance and compare them with other existing models.